{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,4]],"date-time":"2025-11-04T16:17:58Z","timestamp":1762273078000,"version":"build-2065373602"},"reference-count":91,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2023,1,31]],"date-time":"2023-01-31T00:00:00Z","timestamp":1675123200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This study demonstrates a circum-Arctic monitoring framework for quantifying annual change of permafrost-affected coasts at a spatial resolution of 10 m. Frequent cloud coverage and challenging lighting conditions, including polar night, limit the usability of optical data in Arctic regions. For this reason, Synthetic Aperture RADAR (SAR) data in the form of annual median and standard deviation (sd) Sentinel-1 (S1) backscatter images covering the months June\u2013September for the years 2017\u20132021 were computed. Annual composites for the year 2020 were hereby utilized as input for the generation of a high-quality coastline product via a Deep Learning (DL) workflow, covering 161,600 km of the Arctic coastline. The previously computed annual S1 composites for the years 2017 and 2021 were employed as input data for the Change Vector Analysis (CVA)-based coastal change investigation. The generated DL coastline product served hereby as a reference. Maximum erosion rates of up to 67 m per year could be observed based on 400 m coastline segments. Overall highest average annual erosion can be reported for the United States (Alaska) with 0.75 m per year, followed by Russia with 0.62 m per year. Out of all seas covered in this study, the Beaufort Sea featured the overall strongest average annual coastal erosion of 1.12 m. Several quality layers are provided for both the DL coastline product and the CVA-based coastal change analysis to assess the applicability and accuracy of the output products. The predicted coastal change rates show good agreement with findings published in previous literature. The proposed methods and data may act as a valuable tool for future analysis of permafrost loss and carbon emissions in Arctic coastal environments.<\/jats:p>","DOI":"10.3390\/rs15030818","type":"journal-article","created":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T05:33:53Z","timestamp":1675229633000},"page":"818","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Circum-Arctic Monitoring Framework for Quantifying Annual Erosion Rates of Permafrost Coasts"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5065-0966","authenticated-orcid":false,"given":"Marius","family":"Philipp","sequence":"first","affiliation":[{"name":"Department of Remote Sensing, Institute of Geography and Geology, University of W\u00fcrzburg, Am Hubland, 97074 W\u00fcrzburg, Germany"},{"name":"German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), Muenchener Strasse 20, 82234 Wessling, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5733-7136","authenticated-orcid":false,"given":"Andreas","family":"Dietz","sequence":"additional","affiliation":[{"name":"German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), Muenchener Strasse 20, 82234 Wessling, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6626-3052","authenticated-orcid":false,"given":"Tobias","family":"Ullmann","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing, Institute of Geography and Geology, University of W\u00fcrzburg, Am Hubland, 97074 W\u00fcrzburg, Germany"}]},{"given":"Claudia","family":"Kuenzer","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing, Institute of Geography and Geology, University of W\u00fcrzburg, Am Hubland, 97074 W\u00fcrzburg, Germany"},{"name":"German Remote Sensing Data Center (DFD), German Aerospace Center (DLR), Muenchener Strasse 20, 82234 Wessling, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Bartsch, A., H\u00f6fler, A., Kroisleitner, C., and Trofaier, A.M. (2016). Land cover mapping in northern high latitude permafrost regions with satellite data: Achievements and remaining challenges. Remote Sens., 8.","DOI":"10.3390\/rs8120979"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.rse.2017.05.021","article-title":"Progress in space-borne studies of permafrost for climate science: Towards a multi-ECV approach","volume":"203","author":"Trofaier","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1038\/nature14338","article-title":"Climate change and the permafrost carbon feedback","volume":"520","author":"Schuur","year":"2015","journal-title":"Nature"},{"key":"ref_4","unstructured":"P\u00f6rtner, H.O., Roberts, D.C., Masson-Delmotte, V., Zhai, P., Tignor, M., Poloczanska, E., Mintenbeck, K., Nicolai, M., Okem, A., and Petzold, J. (2019). IPCC Special Report on the Ocean and Cryosphere in a Changing Climate, IPCC Intergovernmental Panel on Climate Change (IPCC)."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1002\/ppp.689","article-title":"Permafrost thermal state in the polar Northern Hemisphere during the international polar year 2007\u20132009: A synthesis","volume":"21","author":"Romanovsky","year":"2010","journal-title":"Permafr. Periglac. Process."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-018-08240-4","article-title":"Permafrost is warming at a global scale","volume":"10","author":"Biskaborn","year":"2019","journal-title":"Nat. Commun."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"5608","DOI":"10.1175\/JCLI-D-12-00341.1","article-title":"Diagnosing present and future permafrost from climate models","volume":"26","author":"Slater","year":"2013","journal-title":"J. Clim."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/j.rse.2015.07.019","article-title":"Distribution of near-surface permafrost in Alaska: Estimates of present and future conditions","volume":"168","author":"Pastick","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1038\/499401a","article-title":"Vast costs of Arctic change","volume":"499","author":"Whiteman","year":"2013","journal-title":"Nature"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"4297","DOI":"10.5194\/bg-10-4297-2013","article-title":"Short-and long-term thermo-erosion of ice-rich permafrost coasts in the Laptev Sea region","volume":"10","author":"Overduin","year":"2013","journal-title":"Biogeosciences"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Novikova, A., Belova, N., Baranskaya, A., Aleksyutina, D., Maslakov, A., Zelenin, E., Shabanova, N., and Ogorodov, S. (2018). Dynamics of permafrost coasts of Baydaratskaya Bay (Kara Sea) based on multi-temporal remote sensing data. Remote Sens., 10.","DOI":"10.3390\/rs10091481"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1016\/j.geomorph.2016.02.014","article-title":"Coastal erosion and mass wasting along the Canadian Beaufort Sea based on annual airborne LiDAR elevation data","volume":"293","author":"Obu","year":"2017","journal-title":"Geomorphology"},{"key":"ref_13","unstructured":"Jones, B.M., Irrgang, A.M., Farquharson, L.M., Lantuit, H., Whalen, D., Ogorodov, S., Grigoriev, M., Tweedie, C., Gibbs, A.E., and Strzelecki, M.C. (2020). Coastal Permafrost Erosion, Arctic Report Card; Pacific Coastal and Marine Science Center."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1007\/s12237-010-9362-6","article-title":"The Arctic coastal dynamics database: A new classification scheme and statistics on Arctic permafrost coastlines","volume":"35","author":"Lantuit","year":"2012","journal-title":"Estuaries Coasts"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1038\/s43017-021-00232-1","article-title":"Drivers, dynamics and impacts of changing Arctic coasts","volume":"3","author":"Irrgang","year":"2022","journal-title":"Nat. Rev. Earth Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"GL034791","DOI":"10.1029\/2008GL034791","article-title":"Sea ice drift in the Arctic since the 1950s","volume":"35","author":"Hakkinen","year":"2008","journal-title":"Geophys. Res. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1038\/ngeo2234","article-title":"Recent Arctic amplification and extreme mid-latitude weather","volume":"7","author":"Cohen","year":"2014","journal-title":"Nat. Geosci."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.gloplacha.2011.03.004","article-title":"Processes and impacts of Arctic amplification: A research synthesis","volume":"77","author":"Serreze","year":"2011","journal-title":"Glob. Planet. Chang."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1525\/elementa.191","article-title":"Projected sea surface temperatures over the 21st century: Changes in the mean, variability and extremes for large marine ecosystem regions of Northern Oceans","volume":"6","author":"Alexander","year":"2018","journal-title":"Elem. Sci. Anthr."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.margeo.2018.07.007","article-title":"Temporal and spatial variability in coastline response to declining sea-ice in northwest Alaska","volume":"404","author":"Farquharson","year":"2018","journal-title":"Mar. Geol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"GL037820","DOI":"10.1029\/2009GL037820","article-title":"A sea ice free summer Arctic within 30 years?","volume":"36","author":"Wang","year":"2009","journal-title":"Geophys. Res. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"GL052868","DOI":"10.1029\/2012GL052868","article-title":"A sea ice free summer Arctic within 30 years: An update from CMIP5 models","volume":"39","author":"Wang","year":"2012","journal-title":"Geophys. Res. Lett."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.coldregions.2014.03.003","article-title":"Landfast sea ice extent in the Chukchi and Beaufort Seas: The annual cycle and decadal variability","volume":"103","author":"Mahoney","year":"2014","journal-title":"Cold Reg. Sci. Technol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s43247-021-00183-x","article-title":"Arctic open-water periods are projected to lengthen dramatically by 2100","volume":"2","author":"Crawford","year":"2021","journal-title":"Commun. Earth Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1038\/nclimate2848","article-title":"Mapping the future expansion of Arctic open water","volume":"6","author":"Barnhart","year":"2016","journal-title":"Nat. Clim. Chang."},{"key":"ref_26","unstructured":"Forbes, D.L. (2011). State of the Arctic Coast 2010: Scientific Review and Outlook, Institute of Coastal Research. Land-Ocean Interactions in the Coastal Zone."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"7005","DOI":"10.1038\/s41467-022-34386-3","article-title":"Sea-level rise will likely accelerate rock coast cliff retreat rates","volume":"13","author":"Shadrick","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_28","unstructured":"Oppenheimer, M., Glavovic, B., Hinkel, J., van de Wal, R., Magnan, A.K., Abd-Elgawad, A., Cai, R., Cifuentes-Jara, M., Deconto, R.M., and Ghosh, T. (2019). IPCC Special Report on the Ocean and Cryosphere in a Changing Climate, IPCC."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"115001","DOI":"10.1088\/1748-9326\/aae471","article-title":"A decade of remotely sensed observations highlight complex processes linked to coastal permafrost bluff erosion in the Arctic","volume":"13","author":"Jones","year":"2018","journal-title":"Environ. Res. Lett."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1002\/ppp.1914","article-title":"Remote sensing of landscape change in permafrost regions","volume":"27","author":"Jorgenson","year":"2016","journal-title":"Permafr. Periglac. Process."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1144\/SP388.13","article-title":"Coastal changes in the Arctic","volume":"388","author":"Overduin","year":"2014","journal-title":"Geol. Soc. Lond. Spec. Publ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1038\/nclimate3188","article-title":"Collapsing arctic coastlines","volume":"7","author":"Fritz","year":"2017","journal-title":"Nat. Clim. Chang."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"900","DOI":"10.1007\/s12237-015-0046-0","article-title":"Erosion and flooding\u2014Threats to coastal infrastructure in the Arctic: A case study from Herschel Island, Yukon Territory, Canada","volume":"39","author":"Radosavljevic","year":"2016","journal-title":"Estuaries Coasts"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1038\/s41558-022-01281-0","article-title":"Increase in Arctic coastal erosion and its sensitivity to warming in the twenty-first century","volume":"12","author":"Nielsen","year":"2022","journal-title":"Nat. Clim. Chang."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"406","DOI":"10.1002\/2017JG004166","article-title":"Coastal erosion of permafrost soils along the Yukon Coastal Plain and fluxes of organic carbon to the Canadian Beaufort Sea","volume":"123","author":"Couture","year":"2018","journal-title":"J. Geophys. Res. Biogeosci."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"11244","DOI":"10.1029\/2019GL084303","article-title":"Rapid CO2 release from eroding permafrost in seawater","volume":"46","author":"Tanski","year":"2019","journal-title":"Geophys. Res. Lett."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1038\/nature11392","article-title":"Activation of old carbon by erosion of coastal and subsea permafrost in Arctic Siberia","volume":"489","author":"Vonk","year":"2012","journal-title":"Nature"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1038\/s41467-020-20470-z","article-title":"Around one third of current Arctic Ocean primary production sustained by rivers and coastal erosion","volume":"12","author":"Terhaar","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"034014","DOI":"10.1088\/1748-9326\/11\/3\/034014","article-title":"Biomass offsets little or none of permafrost carbon release from soils, streams, and wildfire: An expert assessment","volume":"11","author":"Abbott","year":"2016","journal-title":"Environ. Res. Lett."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Philipp, M., Dietz, A., Ullmann, T., and Kuenzer, C. (2022). Automated Extraction of Annual Erosion Rates for Arctic Permafrost Coasts Using Sentinel-1, Deep Learning, and Change Vector Analysis. Remote Sens., 14.","DOI":"10.3390\/rs14153656"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"e2019RG000652","DOI":"10.1029\/2019RG000652","article-title":"Space-Based Observations for Understanding Changes in the Arctic-Boreal Zone","volume":"58","author":"Duncan","year":"2020","journal-title":"Rev. Geophys."},{"key":"ref_42","unstructured":"Westermann, S., Duguay, C.R., Grosse, G., and K\u00e4\u00e4b, A. (2014). Remote Sensing of the Cryosphere, John Wiley & Sons, Ltd."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1002\/ppp.619","article-title":"Remote sensing of permafrost-related problems and hazards","volume":"19","year":"2008","journal-title":"Permafr. Periglac. Process."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"143","DOI":"10.3389\/fenvs.2020.00143","article-title":"Feasibility study for the application of Synthetic Aperture Radar for coastal erosion rate quantification across the Arctic","volume":"8","author":"Bartsch","year":"2020","journal-title":"Front. Environ. Sci."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"962208","DOI":"10.3389\/feart.2022.962208","article-title":"ArcticBeach v1. 0: A physics-based parameterization of pan-Arctic coastline erosion","volume":"10","author":"Rolph","year":"2022","journal-title":"Front. Earth Sci."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"877","DOI":"10.1111\/tgis.12073","article-title":"A comprehensive framework for intrinsic OpenStreetMap quality analysis","volume":"18","author":"Barron","year":"2014","journal-title":"Trans. GIS"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1080\/07421222.1993.11517988","article-title":"Comparing the modeling performance of regression and neural networks as data quality varies: A business value approach","volume":"10","author":"Bansal","year":"1993","journal-title":"J. Manag. Inf. Syst."},{"key":"ref_48","unstructured":"Rozhnova, M. (2022, November 28). Impact of Dataset Errors on Model Accuracy. Available online: https:\/\/medium.com\/deelvin-machine-learning\/impact-of-dataset-errors-on-model-accuracy-723fef5e0b28."},{"key":"ref_49","unstructured":"ESA Communications (2022, October 14). Sentinel-1: ESA\u2019s Radar Observatory Mission for GMES Operational Services. Available online: https:\/\/sentinel.esa.int\/documents\/247904\/349449\/S1_SP-1322_1.pdf."},{"key":"ref_50","unstructured":"European Space Agency (2022, October 14). Sentinel-2 User Handbook. Available online: https:\/\/sentinels.copernicus.eu\/documents\/247904\/685211\/Sentinel-2_User_Handbook."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"3966","DOI":"10.1080\/01431161.2011.636081","article-title":"Google Earth as a virtual globe tool for Earth science applications at the global scale: Progress and perspectives","volume":"33","author":"Yu","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_52","unstructured":"Obu, J., Westermann, S., Barboux, C., Bartsch, A., Delaloye, R., Grosse, G., Heim, B., Hugelius, G., Irrgang, A., and K\u00e4\u00e4b, A. (ESA Permafrost Climate Change Initiative (Permafrost_cci): Permafrost Extent for the Northern Hemisphere, 2021). ESA Permafrost Climate Change Initiative (Permafrost_cci): Permafrost Extent for the Northern Hemisphere, v3.0\u2019."},{"key":"ref_53","unstructured":"OpenStreetMap Contributors (2022, November 12). Planet Dump. Available online: https:\/\/www.openstreetmap.org."},{"key":"ref_54","unstructured":"National Oceanic and Atmospheric Administration (NOAA) (2022, October 14). Water Levels\u2014NOAA Tides, and Currents, Available online: https:\/\/tidesandcurrents.noaa.gov\/stations.html?type=Water+Levels."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.gloplacha.2006.07.018","article-title":"The GLIMS geospatial glacier database: A new tool for studying glacier change","volume":"56","author":"Raup","year":"2007","journal-title":"Glob. Planet. Chang."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"JC003384","DOI":"10.1029\/2005JC003384","article-title":"Sea ice remote sensing using AMSR-E 89-GHz channels","volume":"113","author":"Spreen","year":"2008","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_57","unstructured":"Flanders Marine Institute (2022, November 15). IHO Sea Areas, Version 3. Available online: https:\/\/www.marineregions.org\/."},{"key":"ref_58","unstructured":"Natural Earth (2020, August 28). Natural Earth I with Shaded Relief and Water. Available online: https:\/\/www.naturalearthdata.com\/downloads\/10m-raster-data\/10m-natural-earth-1\/."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1109\/LGRS.2016.2637439","article-title":"SeNet: Structured edge network for sea\u2013land segmentation","volume":"14","author":"Cheng","year":"2016","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"3954","DOI":"10.1109\/JSTARS.2018.2833382","article-title":"DeepUNet: A deep fully convolutional network for pixel-level sea-land segmentation","volume":"11","author":"Li","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Baumhoer, C.A., Dietz, A.J., Kneisel, C., and Kuenzer, C. (2019). Automated extraction of antarctic glacier and ice shelf fronts from sentinel-1 imagery using deep learning. Remote Sens., 11.","DOI":"10.3390\/rs11212529"},{"key":"ref_62","first-page":"4300514","article-title":"HED-UNet: Combined Segmentation and Edge Detection for Monitoring the Antarctic Coastline","volume":"60","author":"Heidler","year":"2021","journal-title":"IEEE Trans. Geosci. Remote. Sens."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., and Brox, T. (2015, January 5\u20139). U-net: Convolutional networks for biomedical image segmentation. Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention, Munich, Germany.","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"527","DOI":"10.5194\/nhess-5-527-2005","article-title":"Remote sensing of glacier- and permafrost-related hazards in high mountains: An overview","volume":"5","author":"Huggel","year":"2005","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_65","unstructured":"Google Developers (2022, November 25). Sentinel-1 Algorithms. Available online: https:\/\/developers.google.com\/earth-engine\/guides\/sentinel1."},{"key":"ref_66","unstructured":"OpenStreetMap (2023, January 22). Contributors. Available online: https:\/\/wiki.openstreetmap.org\/wiki\/Contributors#Denmark."},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Mooney, P., Corcoran, P., and Winstanley, A.C. (2010, January 2\u20135). Towards quality metrics for OpenStreetMap. Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems, San Jose, CA, USA.","DOI":"10.1145\/1869790.1869875"},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., and Sun, J. (2016, January 27\u201330). Deep residual learning for image recognition. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref_69","unstructured":"Simonyan, K., and Zisserman, A. (2014). Very deep convolutional networks for large-scale image recognition. arXiv."},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., and Wojna, Z. (2016, January 27\u201330). Rethinking the Inception Architecture for Computer Vision. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Ioffe, S., Vanhoucke, V., and Alemi, A.A. (2017, January 4\u20139). Inception-v4, inception-resnet and the impact of residual connections on learning. Proceedings of the Thirty-first AAAI Conference on Artificial Intelligence, San Francisco, CA, USA.","DOI":"10.1609\/aaai.v31i1.11231"},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Huang, G., Liu, Z., Van Der Maaten, L., and Weinberger, K.Q. (2017, January 21\u201326). Densely connected convolutional networks. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Xie, S., Girshick, R., Doll\u00e1r, P., Tu, Z., and He, K. (2017, January 21\u201326). Aggregated residual transformations for deep neural networks. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.634"},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., and Sun, G. (2018, January 18\u201322). Squeeze-and-excitation networks. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref_75","unstructured":"Wegmann, M., Leutner, B., and Dech, S. (2016). Remote Sensing and GIS for Ecologists: Using Open Source Software, Pelagic Publishing Ltd."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1109\/LGRS.2010.2068537","article-title":"Change vector analysis in posterior probability space: A new method for land cover change detection","volume":"8","author":"Chen","year":"2010","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_77","unstructured":"GLIMS Consortium (2022, November 07). GLIMS Glacier Database, Version 1. Available online: https:\/\/nsidc.org\/data\/NSIDC-0272\/versions\/1."},{"key":"ref_78","unstructured":"National Oceanic and Atmospheric Administration (NOAA) (2022, October 14). Tidal Datums\u2014NOAA Tides, and Currents, Available online: https:\/\/tidesandcurrents.noaa.gov\/datum_options.html."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"9431","DOI":"10.3390\/rs70709431","article-title":"Sentinel-1A product geolocation accuracy: Commissioning phase results","volume":"7","author":"Schubert","year":"2015","journal-title":"Remote Sens."},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Schubert, A., Miranda, N., Geudtner, D., and Small, D. (2017). Sentinel-1A\/B combined product geolocation accuracy. Remote Sens., 9.","DOI":"10.3390\/rs9060607"},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Richards, J.A. (2009). Remote Sensing with Imaging Radar, Springer.","DOI":"10.1007\/978-3-642-02020-9"},{"key":"ref_82","unstructured":"Lighthill, M.J., and Lighthill, J. (2001). Waves in Fluids, Cambridge University Press."},{"key":"ref_83","first-page":"1245924","article-title":"PLANET: Improved convolutional neural networks with image enhancement for image classification","volume":"2020","author":"Tang","year":"2020","journal-title":"Math. Probl. Eng."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1016\/S0305-0483(99)00019-5","article-title":"Data quality in neural network models: Effect of error rate and magnitude of error on predictive accuracy","volume":"27","author":"Klein","year":"1999","journal-title":"Omega"},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"1856","DOI":"10.1109\/TMI.2019.2959609","article-title":"Unet++: Redesigning skip connections to exploit multiscale features in image segmentation","volume":"39","author":"Zhou","year":"2019","journal-title":"IEEE Trans. Med Imaging"},{"key":"ref_86","doi-asserted-by":"crossref","unstructured":"Wang, J., Li, D., Cao, W., Lou, X., Shi, A., and Zhang, H. (2022). Remote Sensing Analysis of Erosion in Arctic Coastal Areas of Alaska and Eastern Siberia. Remote Sens., 14.","DOI":"10.3390\/rs14030589"},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"779","DOI":"10.1002\/2017JF004326","article-title":"Variability in rates of coastal change along the Yukon coast, 1951 to 2015","volume":"123","author":"Irrgang","year":"2018","journal-title":"J. Geophys. Res. Earth Surf."},{"key":"ref_88","unstructured":"European Space Agency (2022, December 02). Observation Scenario Archive. Available online: https:\/\/sentinels.copernicus.eu\/web\/sentinel\/missions\/sentinel-1\/observation-scenario\/archive."},{"key":"ref_89","unstructured":"Alaska Satellite Facility (2022, November 28). Sentinel-1\u2014Acquisition Maps. Available online: https:\/\/asf.alaska.edu\/data-sets\/sar-data-sets\/sentinel-1\/sentinel-1-acquisition-maps\/."},{"key":"ref_90","unstructured":"European Space Agency (2022, November 29). Mission Ends for Copernicus Sentinel-1B Satellite. Available online: https:\/\/www.esa.int\/Applications\/Observing_the_Earth\/Copernicus\/Sentinel-1\/Mission_ends_for_Copernicus_Sentinel-1B_satellite."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1111\/j.1365-3121.1996.tb00739.x","article-title":"A consistent map of the postglacial uplift of Fennoscandia","volume":"8","author":"Ekman","year":"1996","journal-title":"Terra Nova"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/3\/818\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:20:21Z","timestamp":1760120421000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/3\/818"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,31]]},"references-count":91,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2023,2]]}},"alternative-id":["rs15030818"],"URL":"https:\/\/doi.org\/10.3390\/rs15030818","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2023,1,31]]}}}